CN114624779A - Pre-stack multi-parameter inversion method for balanced model constraint - Google Patents
Pre-stack multi-parameter inversion method for balanced model constraint Download PDFInfo
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Abstract
The invention provides a pre-stack multi-parameter inversion method for balanced model constraint, which comprises the following steps: step 1, constructing an initial iteration model and a broadband balance constraint model by using seismic structure interpretation and well logging information; step 2, constructing a target function with double loss functions of seismic residual and broadband balance model residual; and 3, performing objective function optimization solving according to the inverse wavelet, the prestack earthquake and the constraint model to obtain the broadband longitudinal and transverse wave velocity and density. The pre-stack multi-parameter inversion method based on the equilibrium model constraint increases the broadband multi-parameter model constraint on the basis of the pre-stack seismic constraint, can adjust the contribution of two kinds of constraint information by adjusting the equilibrium parameter, and has important significance for expanding the seismic inversion frequency band and improving the inversion resolution by utilizing seismic, well logging and full waveform inversion information.
Description
Technical Field
The invention relates to the field of seismic data processing, in particular to a pre-stack multi-parameter inversion method for equilibrium model constraint.
Background
Logging constraint seismic inversion is an important reservoir prediction description technology in oil and gas exploration and development, and the conventional inversion target function construction mostly takes forward seismic and actual seismic residual errors of parameters to be inverted as loss functions, and then is optimized and solved, so that seismic information is main known information in the inversion process. Earthquake is data which has strong three-dimensional space description capacity but limited seismic frequency band and geological resolution. Because only seismic information is adopted in the conventional inversion, the final inversion result tends to a seismic frequency band, the inversion frequency band and the inversion resolution are limited, and high-resolution identification and description of a reservoir stratum are not utilized. With the improvement of the oil and gas exploration degree, a plurality of oil and gas exploration development areas also have a large amount of logging information besides seismic information, accumulate a large amount of geological structure deposition cognition and interpretation results, can be used for constructing a broadband model, longitudinally reflect the change of a thick stratum and a thin reservoir, only the model change in a transverse three-dimensional space is not natural and accurate enough, and three-dimensional seismic information is required to play a role, so that an inversion method which simultaneously and efficiently utilizes the seismic and model information is required, the inversion frequency band is widened, and the inversion precision and the reservoir resolution capability are improved.
In the application No.: the Chinese patent application of CN201911315267.9 relates to a pre-stack seismic inversion method for shale reservoirs, which comprises the following specific implementation steps: the method comprises the following steps: acquiring prestack seismic data of a research work area, wherein the data is gather data containing a full wave effect; step two: setting a depth range in which inversion needs to be carried out, and establishing an elastic parameter depth domain initial model in the set depth range by using the collected logging data; step three: calculating a time-angle domain reflection coefficient sequence by using a recursive matrix based on the initial model; step four: calculating a forward modeling record gather corresponding to the initial model based on the pre-stack seismic trace gather and the acquired reflection coefficient sequence, and calculating a pre-stack trace gather and a modeling record data residual error item; step five: calculating a forward partial derivative of the recursive matrix by using the initial model parameters; step six: calculating a Jacobian matrix and a pseudo Hessian matrix of the target function based on the target function and the positive operator partial derivative; step seven: calculating the updating direction of the model and updating the model parameters; step eight: and repeating the third step to the seventh step, performing inversion iteration for the next time until the model error is reduced to a preset range, stopping iteration, and outputting an inversion result of the parameters. According to the method, a target function is constructed by taking a prestack gather and a logging model forward modeling simulation seismic record residual as a loss function, a seismic frequency band part inversion model is updated by utilizing seismic information, low-frequency and high-frequency information of the logging model are completely reserved, although the inversion result is also wide-frequency, the inversion result does not consider the construction precision of the logging model under the conditions of complex geology and less logging information, particularly the reliability of the high-frequency information, and the final inversion result is high in resolution, but more uncertain information, so that the reservoir prediction multi-solution is caused.
In the application No.: CN201710910382.5, chinese patent application, relates to a prestack seismic inversion method and system. The method can comprise the following steps: converting the pre-stack seismic gathers into angle gathers, grouping and stacking to obtain a plurality of angle gather groups; establishing a shale gas reservoir model, obtaining the density sensitivity of an elastic impedance equation, and selecting a density inversion equation; according to a density inversion equation, performing elastic impedance inversion on the multiple angle gather groups to obtain elastic impedance data volumes of the multiple angle gather groups; establishing a relational expression among longitudinal wave velocity, transverse wave velocity, density and an incident angle, and linearizing to obtain a linearized elastic impedance equation; writing the longitudinal wave velocity, the transverse wave velocity and the density as the weighted sum of the elastic impedance; obtaining an elastic impedance weighting coefficient based on the well side channel elastic impedance inversion result and the logging data; and obtaining the reservoir elasticity parameter based on the weighted sum and the weighted coefficient. The method has the advantages of multiple links and complex process, can not directly utilize pre-stack seismic data to synchronously invert to obtain longitudinal wave velocity and transverse wave velocity and density, needs to calculate elastic impedance corresponding to multiple angles, then utilizes a linearized elastic impedance equation to solve elastic parameters such as the longitudinal wave velocity, the transverse wave velocity and the density, has large practical application workload and a plurality of multi-process errors, and influences inversion precision.
In the application No.: CN201611116496.4, a chinese patent application, relates to a horizontal fracture seismic prestack inversion method and device, including: acquiring the physical property parameters of the underground medium of the target work area according to the logging information of the target work area; the subsurface medium physical parameters include: physical property parameters of each formation and fracture parameters of each fracture; extracting seismic wavelets of a well-side seismic gather in a target work area according to the acquired physical property parameters of the underground medium; establishing a stratum initial model of a target work area according to the obtained physical property parameters of the underground medium; and according to the stratum initial model, the seismic wavelets of the seismic channels beside the well and the actual seismic channel gather, performing inversion to obtain a stratum model of the physical property parameters of the underground real medium in the target work area. The method is mainly invented for horizontal fracture prediction, and the final inversion parameters, except the longitudinal wave velocity, the transverse wave velocity and the density, also obtain the horizontal fracture parameters.
Therefore, a novel balance model constrained prestack multi-parameter inversion method is invented, and the technical problems are solved.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a pre-stack multi-parameter inversion method for balanced model constraints, which can efficiently utilize seismic and broadband model information to obtain various elastic parameters with strong broadband reservoir space description capability through inversion.
The object of the invention can be achieved by the following technical measures: a pre-stack multi-parameter inversion method constrained by a balanced model comprises the following steps: step 1, constructing an initial iteration model and a broadband balance constraint model by using seismic structure interpretation and well logging information; step 2, constructing a target function with double loss functions of seismic residual and broadband balance model residual; and 3, inputting the inverse wavelet, the prestack earthquake and the constraint model, and performing objective function optimization solution to obtain the broadband longitudinal and transverse wave velocity and density.
The object of the invention can also be achieved by the following technical measures:
in step 1, an initial iteration model and a broadband multi-parameter balance constraint model are constructed based on seismic structure interpretation and well logging information, and constraints are provided for the application of a prestack multi-parameter inversion method constrained by the balance model.
In step 2, the objective function includes the seismic residual and the balance model residual terms:
in the formula, S (VP, VS, ρ)ΔTo expect seismic response, D1For prestack seismic recording, D2For forward modeling of the balanced constraint model, VP represents the velocity of longitudinal waves to be inverted, VS represents the velocity of transverse waves to be inverted, ρ is the density to be inverted, and β is a balance parameter.
In step 2, a balance parameter β is set in the objective function, the weights of the two loss functions are controlled, the contribution of the earthquake and the balance model are distributed, the value range is 0-1, the balance model does not contribute to inversion when β is 0, and the contribution of the balance model and the earthquake to inversion respectively accounts for 50% when β is 1.
In step 3, taylor expansion is carried out on the expected model response, and high-order terms are omitted, so that a linear expression of the expected model response of the initial model response, the Jacobian matrix and the model disturbance quantity is obtained:
S(VP,VS,ρ)Δ＝S(VP,VS,ρ)+GΔM＝WR(VP,VS,ρ)+GΔM (2)
wherein, W is the actual pre-stack seismic extraction wavelet, and G is a Jacobian matrix formed by forward modeling seismic longitudinal wave velocity, transverse wave velocity and density partial derivatives of an iterative model; Δ M is a matrix composed of longitudinal wave velocity, transverse wave velocity and density disturbance quantity of each sampling point, and is expressed as:
ΔM＝[ΔVP1 ΔVS1 Δρ1 ΔVP2 ΔVS2 Δρ2 … ΔVPn ΔVSn Δρn]T。
in step 3, the formula (2) is taken into the formula (1), and the first-order partial derivative is solved to be zero, so that an inversion parameter model disturbance quantity solving formula can be obtained:
the initial iteration model is updated by solving the disturbance quantity, and the formula is as follows
Wherein m ═ is (VP)i，VSi，VPi+1，VSi+1，ρi+1，ρi) Representing the longitudinal wave velocity, the transverse wave velocity and the density parameter of the ith sampling point and the next adjacent sampling point; λ is the regularization parameter and k is the number of iterations.
And in step 3, continuously updating iteration on the iteration model, and terminating iteration when the iteration times or the objective function meets a certain condition, thereby finally realizing longitudinal wave velocity, transverse wave velocity and density inversion.
Due to the adoption of the technical scheme, the invention has the following advantages: aiming at the problems of high dependence degree of conventional inversion earthquake, narrow inversion result frequency band and low precision, a balance model constraint item is added to an inversion target function, and the final inversion contribution is controlled by a balance parameter control model.
Drawings
FIG. 1 is a flow chart of one embodiment of a balanced model constrained prestack multiparameter inversion method of the present invention;
FIG. 2 is a schematic cross-sectional view of a broadband multi-parameter balanced constraint model constructed according to an embodiment of the present invention;
FIG. 3 is a cross-sectional view of a seismic stack and a multi-parameter inversion result with a balance parameter β of 1 according to an embodiment of the present invention;
fig. 4 is a cross-sectional view of inverse longitudinal velocity contrast when the balance parameter is β 1 and β 0, respectively, according to an embodiment of the present invention.
Detailed Description
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of the stated features, steps, operations, and/or combinations thereof, unless the context clearly indicates otherwise.
Referring to fig. 1, fig. 1 is a flowchart of an embodiment of a balanced model constrained prestack multi-parameter inversion method according to the present invention. The pre-stack multi-parameter inversion method for the constraint of the balanced model comprises the following steps:
step 1, constructing an initial iteration model and a broadband multi-parameter balance constraint model based on seismic structure interpretation and well logging information.
Step 2, constructing a target function with double loss functions of seismic residual and broadband balance model residual;
the inverse objective function is as follows:
in the formula, S (VP, VS, ρ)ΔTo expect seismic response, D1For prestack seismic recording, D2And (3) forward modeling the seismic record for a balanced constraint model, wherein VP represents the velocity of longitudinal waves to be inverted, VS represents the velocity of transverse waves to be inverted, rho is the density to be inverted, beta is a balance parameter, the weights of the two loss functions are controlled, and the value range is 0-1.
And 3, inputting the inverse wavelet, the prestack earthquake, the initial iteration model and the broadband model, and performing objective function optimization solution to obtain broadband longitudinal and transverse wave speeds and densities.
And performing Taylor expansion on the expected model response, and omitting high-order terms to obtain a linearized expression of the response of the expected model response of the initial model response, the Jacobian matrix and the model disturbance quantity:
S(VP,VS,ρ)Δ＝S(VP,VS,ρ)+GΔM＝WR(VP,VS,ρ)+GΔM (2)
w is a broadband wavelet matched with pre-stack seismic energy, and G is a Jacobian matrix formed by forward modeling seismic-to-longitudinal wave velocity, transverse wave velocity and density partial derivatives of an iterative model. Δ M is a matrix composed of longitudinal wave velocity, transverse wave velocity and density disturbance quantity of each sampling point, and is expressed as:
ΔM＝[ΔVP1 ΔVS1 Δρ1 ΔVP2 ΔVS2 Δρ2 … ΔVPn ΔVSn Δρn]T
taking the formula (2) into the formula (1), solving the first-order partial derivative to be zero, and obtaining an inversion parameter model disturbance quantity solving formula:
the initial iteration model is updated by solving the disturbance quantity, and the formula is as follows
Wherein m ═ is (VP)i，VSi，VPi+1，VSi+1，ρi+1，ρi) And the longitudinal wave velocity, the transverse wave velocity and the density parameter of the ith sampling point and the next adjacent sampling point are represented. λ is the regularization parameter and k is the number of iterations.
And continuously updating and iterating the initial model by the target function and the initial 3-parameter model iteration updating formula, terminating the inversion iteration when the iteration times or the target function meets a certain condition, and outputting the final iteration correction model parameters to obtain the longitudinal wave velocity, the transverse wave velocity and the density inversion result.
In specific embodiment 1 to which the present invention is applied, the balanced model constrained prestack multi-parameter inversion method of the present invention includes the following steps:
step 1, constructing a broadband multi-parameter balance constraint model based on construction and logging, processing logging high-frequency cutoff frequency of 120Hz according to the actual reservoir thickness response frequency, reducing thin-layer high-frequency random information, and improving the stability of the broadband model. Meanwhile, an initial iterative model is constructed based on construction and logging, logging high-frequency cutoff is about 10Hz, and logging low-frequency information is only utilized. Fig. 2 is a schematic cross-sectional view of a broadband multi-parameter balance constraint model constructed in an embodiment of the invention, which is a longitudinal wave velocity model, a transverse wave velocity model and a density model, wherein the model is constructed by using 120Hz high-frequency-cut logging information and adopting an interpolation method under the constraint of geological structure, the model has wide frequency band and high resolution, but the model has poor characterization capability on the transverse change of geological space due to few logging samples and can be used as an application balance constraint model of an inversion method.
And 2, constructing a target function with double loss functions of the seismic residual and the broadband balance model residual.
The objective function is as follows:
and (3) deducing and constructing an inversion iterative formula:
D2forward seismic records for the broadband equilibrium constrained model and the broadband inversion wavelet W, which can be denoted as D2WR (VP, VS, ρ). Beta is a balance parameter, controls the weight of the two loss functions and has a value range of 0-1. The initial setting of the balance parameters needs to be determined according to the correlation between the forward earthquake and the actual earthquake of the balance constraint model, the high correlation coefficient indicates that the reliability of the balance model is strong, the value of the balance parameters needs to be increased, and the balance parameters need to be gradually reduced along with the increase of the inversion iteration times. In the present example, two parameter values of β ═ 1 and β ═ 0 are selectively applied.
And 3, inputting the inverse wavelet, the prestack earthquake, the initial iteration model and the broadband constraint model, and performing objective function optimization solution to obtain broadband longitudinal and transverse wave speeds and densities. Fig. 3 shows the multi-parameter inversion result and the seismic stack profile when the equilibrium parameter β is 1, and the wide-band equilibrium model and the seismic each account for 50% of the inversion contribution in an embodiment of the present invention. Compared with a wide-frequency model constructed by only utilizing logging information, the inversion increases the space and increases the constraint of seismic information, the space change of the longitudinal wave velocity, the transverse wave velocity and the density is natural, and meanwhile, compared with the seismic frequency band, the inversion method is wider and the inversion reservoir resolution is high.
Fig. 4 is a velocity contrast profile of an inverted compressional wave with a balance parameter β 1 and β 0, respectively, according to an embodiment of the present invention. When the balance parameter beta is 0, the broadband balance constraint model does not work, namely, the conventional pre-stack multi-parameter inversion based on earthquake, the inversion result only has the low-frequency information and the earthquake frequency band information of the initial well logging iterative model, and the inversion longitudinal wave speed of beta is 1, because the broadband balance model constraint information is added, the longitudinal wave is inverted, and the inversion resolution is higher.
In specific embodiment 2 to which the present invention is applied, the balanced model constrained prestack multi-parameter inversion method of the present invention includes the following steps:
step 1, constructing a low-frequency model and a broadband multi-parameter balance constraint model based on construction and logging. Firstly, respectively constructing a low-frequency longitudinal wave velocity model and a broadband balance longitudinal wave velocity constraint model by utilizing logging information of 10Hz high-frequency-cutoff longitudinal wave velocity and 150Hz high-frequency-cutoff longitudinal wave velocity, transverse wave velocity and density. The high band broadening of the broadband model in this example, the thin layer resolution is stronger, but the uncertainty increases.
And 2, constructing a target function with double loss functions of the seismic residual and the broadband balance model residual.
The objective function is as follows:
and (3) deducing and constructing an inversion iterative formula:
D2forward seismic records for the broadband equilibrium constrained model and the broadband inversion wavelet W, which can be expressed as D2WR (VP, VS, ρ). In the example, beta can be set to be 0.5, so that inversion can be ensured to be deterministic mainly by means of seismic data, and meanwhile, the inversion resolution is improved by properly applying a broadband constraint model.
And 3, inputting the inverse wavelet, the prestack earthquake, the initial iteration model and the broadband constraint model, and performing objective function optimization solution to obtain broadband longitudinal and transverse wave speeds and densities. The inversion result certainty and resolution is between the inversion results with the balance parameters β 0 and β 1.
According to the pre-stack multi-parameter inversion method based on the equilibrium model constraint, the broadband multi-parameter model constraint is added on the basis of the pre-stack seismic constraint, the equilibrium parameters are set by combining the model construction precision, the contribution of two kinds of constraint information of the seismic and logging models can be flexibly and controllably adjusted, and the method has important significance for expanding the seismic inversion frequency band and improving the inversion resolution by using the logging information.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
In addition to the technical features described in the specification, the technology is known to those skilled in the art.
Claims (7)
1. The equilibrium model constrained prestack multi-parameter inversion method is characterized by comprising the following steps:
step 1, constructing an initial iteration model and a broadband balance constraint model by using seismic structure interpretation and well logging information;
step 2, constructing a target function with double loss functions of seismic residual and broadband balance model residual;
and 3, performing optimization solution on the objective function according to the inverse wavelet, the prestack earthquake and the constraint model to obtain the broadband longitudinal and transverse wave velocity and density.
2. The balanced model constrained prestack multiparameter inversion method according to claim 1, characterized in that: in step 1, an initial iteration model and a broadband multi-parameter balance constraint model are constructed based on seismic structure interpretation and well logging information, and constraints are provided for the application of a prestack multi-parameter inversion method constrained by the balance model.
3. The balanced model constrained prestack multiparameter inversion method according to claim 1, characterized in that: in step 2, the objective function includes the seismic residual and the balance model residual terms:
in the formula, S (VP, VS, ρ)ΔTo expect seismic response, D1For prestack seismic recording, D2For forward modeling of the balanced constraint model, VP represents the velocity of longitudinal waves to be inverted, VS represents the velocity of transverse waves to be inverted, ρ is the density to be inverted, and β is a balance parameter.
4. The balanced model constrained prestack multiparameter inversion method according to claim 3, characterized in that: in step 2, a balance parameter β is set in the objective function, the weights of the two loss functions are controlled, the contribution of the earthquake and the balance model are distributed, the value range is 0-1, the balance model does not contribute to inversion when β is 0, and the contribution of the balance model and the earthquake to inversion respectively accounts for 50% when β is 1.
5. The balanced model constrained prestack multiparameter inversion method according to claim 3, characterized in that: in step 3, taylor expansion is carried out on the expected model response, and high-order terms are omitted, so that a linear expression of the expected model response of the initial model response, the Jacobian matrix and the model disturbance quantity is obtained:
S(VP,VS,ρ)Δ＝S(VP,VS,ρ)+GΔM＝WR(VP,VS,ρ)+GΔM (2)
wherein, W is the actual pre-stack seismic extraction wavelet, and G is a Jacobian matrix formed by forward modeling seismic longitudinal wave velocity, transverse wave velocity and density partial derivatives of an iterative model; Δ M is a matrix composed of longitudinal wave velocity, transverse wave velocity and density disturbance quantity of each sampling point, and is expressed as:
ΔM＝[ΔVP1 ΔVS1 Δρ1 ΔVP2 ΔVS2 Δρ2 … ΔVPn ΔVSn Δρn]T。
6. the balanced model constrained prestack multiparameter inversion method according to claim 5, characterized in that: in step 3, the formula (2) is taken into the formula (1), and the first-order partial derivative is solved to be zero, so that an inversion parameter model disturbance quantity solving formula is obtained:
wherein m ═ is (VP)i，VSi，VPi+1，VSi+1，ρi+1，ρi) Representing the longitudinal wave velocity, the transverse wave velocity and the density parameter of the ith sampling point and the next adjacent sampling point; λ is the regularization parameter and k is the number of iterations.
7. The balanced model constrained prestack multiparameter inversion method according to claim 5, characterized in that: in step 3, the initial iteration model is continuously updated, and when the iteration times or the objective function meets a certain condition, the iteration is terminated, and the inversion of the longitudinal wave velocity, the transverse wave velocity and the density is finally realized.
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